Measurement and Multivariate Analysis

1. Front Matter

   Pages ii-xvi

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2. Keynote Papers

   1. Categories and Quantities

      • John C. Gower

      Pages 1-12

   2. Questionnaire Construction, Data Collection and Data Analysis: An Approach by the Idea of Data Science

      • Chikio Hayashi

      Pages 13-24

3. Introduction

   1. Measurement and Multivariate Analysis

      • Shizuhiko Nishisato

      Pages 25-36

4. Scaling

   1. An Intelligent Clustering Technique Based on Dual Scaling

      • Hans-Joachim Mucha

      Pages 37-46

   2. Homogeneity and Smoothness Analysis for Quantifying a Longitudinal Categorical Variable

      • Kohei Adachi

      Pages 47-56

   3. Partial Multiple Correspondence Analysis

      • Haruo Yanai, Tadahiko Maeda

      Pages 57-68

   4. Studying Triadic Distance Models Under a Likelihood Function

      • Mark de Rooij

      Pages 69-76

   5. A Generalized Modification of Scheffé’s Paired Comparisons: A theoretical approach to decrease the number of experiments

      • Masaya Iizuka, Katsumi Ujiie

      Pages 77-86

   6. Analysing Dependence in Large Contingency Tables: NonSymmetric Correspondence Analysis and Regression with Optimal Scaling

      • Pieter M. Kroonenberg

      Pages 87-96

   7. Multidimensional Scaling with Different Orientations of Dimensions for Symmetric and Asymmetric Relationships

      • Akinori Okada, Tadashi Imaizumi

      Pages 97-106

   8. Complex Space Models for the Analysis of Asymmetry

      • Naohito Chino

      Pages 107-114

5. Structural Analysis

   1. Structural Equation Modeling by Extended Redundancy Analysis

      • Heungsun Hwang, Yoshio Takane

      Pages 115-124

   2. Redundancy Index in Canonical Correlation Analysis with Linear Constraints

      • Akio Suzukawa, Nobuhiro Taneichi

      Pages 125-132

   3. Regularized Kernel Discriminant Analysis with Optimally Scaled Data

      • Halima Bensmail, Hamparsum Bozdogan

      Pages 133-144

   4. Dimension Reduction in Hierarchical Linear Models

      • Yoshio Takane, Michael A. Hunter

      Pages 145-154

   5. Time Dependent Principal Component Analysis

      • Yasumasa Baba, Takahiro Nakamura

      Pages 155-162

   6. Borrowing Strength from Images to Facilitate Exploratory Structural Analysis of Binary Variables

      • Robert M. Pruzek

      Pages 163-174

   7. Comparison of Construct Mean Scores Across Populations: A Conceptual Framework

      • Alain De Beuckelaer

      Pages 175-182

   8. Nonlinear Generalized Canonical Correlation Analysis by Neural Network Models

      • Yoshio Takane, Yuriko Oshima-Takane

      Pages 183-190

Diversity is characteristic of the information age and also of statistics. To date, the social sciences have contributed greatly to the development of handling data under the rubric of measurement, while the statistical sciences have made phenomenal advances in theory and algorithms. Measurement and Multivariate Analysis promotes an effective interplay between those two realms of research-diversity with unity. The union and the intersection of those two areas of interest are reflected in the papers in this book, drawn from an international conference in Banff, Canada, with participants from 15 countries. In five major categories - scaling, structural analysis, statistical inference, algorithms, and data analysis - readers will find a rich variety of topics of current interest in the extended statistical community.

• Algorism
• Scaling
• Statistical Interface
• Structural Analysis
• algorithms
• data analysis
• measurement and multivariate analysis conference
• data structures

• Measurement and Evaluation Program CTL, OISE/UT, The University of Toronto, Toronto, Canada

  Shizuhiko Nishisato

• Center for Information on Statistical Sciences, The Institute of Statistical Mathematics, Minato-ku, Tokyo, Japan

  Yasumasa Baba, Koji Kanefuji

• Information Complexity & Model Selection Department of Statistics, 336 SMC, The University of Tennessee, Knoxville, USA

  Hamparsum Bozdogan

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